mirror of
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92d4c2fc5e
- Add new routers: admin, appointments, campaigns - Add storage service and logging config - Add migrations directory and test suite with pytest config - Add supabase_migration_features.sql - Update models, dependencies, config, and existing routers - Remove whatsapp_service (deleted) - Update pyproject.toml and uv.lock dependencies Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
107 lines
3.8 KiB
Python
107 lines
3.8 KiB
Python
"""
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Models router - serves available AI models based on user subscription plan.
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Single source of truth flow:
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config.py (PLAN_LIMITS + MODEL_CATALOG) → this router → frontend
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To add/remove/rename a model, only edit config.py.
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"""
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from fastapi import APIRouter, Depends
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from app.dependencies import get_current_user
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from app.database import get_supabase
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from app.config import PLAN_LIMITS, MODEL_CATALOG, DEFAULT_MODELS
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from typing import List, Optional
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from pydantic import BaseModel
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import logging
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/models", tags=["Models"])
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# ─── Response Models ───────────────────────────────────────────────────────────
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class AvailableModel(BaseModel):
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id: str
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name: str
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provider: str
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badge: str
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description: Optional[str] = None
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is_default: bool = False
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class ModelsResponse(BaseModel):
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models: List[AvailableModel]
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plan: str
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default_model: Optional[str] = None
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has_premium_access: bool
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upgrade_label: Optional[str] = None
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# ─── Helpers ───────────────────────────────────────────────────────────────────
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def _get_user_plan(user_id: str) -> str:
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"""Get user's current subscription plan."""
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supabase = get_supabase()
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result = supabase.table("subscriptions") \
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.select("plan") \
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.eq("user_id", user_id) \
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.eq("status", "active") \
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.execute()
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return result.data[0]["plan"] if result.data else "free"
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# ─── Endpoint ─────────────────────────────────────────────────────────────────
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@router.get("/available", response_model=ModelsResponse)
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async def get_available_models(user=Depends(get_current_user)):
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"""
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Returns the list of AI models the user can access based on their plan.
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Frontend uses this to populate model selection dynamically.
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- free: gets a default model for preview/testing
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- starter: Fireworks AI models
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- pro: Fireworks + OpenAI + Anthropic + Google
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- enterprise: all models
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"""
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plan = _get_user_plan(user.id)
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plan_config = PLAN_LIMITS.get(plan, PLAN_LIMITS["free"])
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allowed_model_ids = plan_config.get("models", [])
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# Enterprise wildcard → resolve to all catalog models
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if "*" in allowed_model_ids:
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allowed_model_ids = list(MODEL_CATALOG.keys())
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# Build model list from catalog metadata
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default_model_id = DEFAULT_MODELS.get(plan)
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models: List[AvailableModel] = []
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for model_id in allowed_model_ids:
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meta = MODEL_CATALOG.get(model_id)
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if not meta:
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logger.warning(f"Model '{model_id}' in PLAN_LIMITS[{plan}] but not in MODEL_CATALOG — skipping")
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continue
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models.append(AvailableModel(
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id=model_id,
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name=meta["name"],
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provider=meta["provider"],
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badge=meta["badge"],
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description=meta.get("description"),
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is_default=(model_id == default_model_id),
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))
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# Determine upgrade messaging
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has_premium = plan in ("business", "agency", "enterprise")
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upgrade_label = None
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if plan == "free":
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upgrade_label = "Upgrade to Starter for more AI models and messaging channels"
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elif plan == "starter":
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upgrade_label = "Upgrade to Business for GPT-4o, Claude, and Gemini"
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return ModelsResponse(
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models=models,
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plan=plan,
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default_model=default_model_id,
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has_premium_access=has_premium,
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upgrade_label=upgrade_label,
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) |